Triple

T4254591
Position Surface form Disambiguated ID Type / Status
Subject Valdemoro E95940 entity
Predicate suburbanAreaOf P5065 FINISHED
Object Madrid E411731 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Madrid | Statement: [Valdemoro, suburbanAreaOf, Madrid]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Madrid
Context triple: [Valdemoro, suburbanAreaOf, Madrid]
  • A. Madrid
    Madrid is the capital and largest city of Spain, renowned for its rich cultural heritage, historic architecture, and vibrant arts and nightlife scenes.
  • B. Madrid
    Madrid is a municipality in the Cundinamarca department of Colombia, located near Bogotá and known for its floriculture and agricultural production.
  • C. Seville
    Seville is a historic Spanish city in Andalusia renowned for its rich Moorish and Christian heritage, iconic landmarks like the Giralda and Alcázar, and vibrant cultural traditions such as flamenco.
  • D. Madrid metropolitan area chosen
    The Madrid metropolitan area is the large urban and economic region centered on Spain’s capital city, encompassing Madrid and its surrounding municipalities and suburbs.
  • E. Barcelona
    Barcelona is a major Spanish Mediterranean city renowned for its distinctive Catalan culture, Gaudí architecture, and vibrant arts and nightlife scenes.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69b3453f759881909b91f01a1e82c036 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34ec036e8819087d8585170707545 completed March 12, 2026, 11:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69b627c8265881908a9bfdb032389151 completed March 15, 2026, 3:30 a.m.
Created at: March 12, 2026, 11:06 p.m.